Big Data Analytics 17CS82 VTU CBCS Notes

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Big Data Analytics 17CS82 – 15CS82 VTU CBCS Notes

Download VTU CBCS notes of Big Data Analytics 17CS82 – 15CS82 VTU CBCS Notes for 8th-semester computer science and engineering, VTU Belagavi.

Solution Manual to Big Data Analytics 17CS82 VTU CBCS Question Bank

Module 1 – Hadoop Distributed File System and Map Reduce Programming

How to install and Configure Hadoop in Ubuntu Step by Step Procedure – Shortcut Method

Components and Architecture Hadoop Distributed File System (HDFS)

What is HDFS? Design Features of HDFS

Following are the contents of module 1 – HDFS

In this module, you will learn the concepts of Hadoop Distributed File System Basics (HDFS). You will understand, how to run map-reduce example programs and benchmarks on HDFS. Also, you will study the Hadoop MapReduce Framework. Finally, simple MapReduce Programming examples are discussed in Java, C++, and python.

Architecture and Components of Hadoop Distributed File System (HDFS) – Big Data Analytics

Design Features of Hadoop Distributed File System (HDFS) – Big Data Analytics

Safe Mode Rack Awareness High NameNode Availability NameNodeFederation CheckPoints Backup Snapshots

Block Replication in Hadoop Distributed File System (HDFS) – Big data Analytics

Hadoop MapReduce Model – Big Data Analytics Tutorial

Word Count Program using Python Streaming Interface – Big Data Analytics Tutorial

WordCount Program in C++ using Pipes interface Hadoop MapReduce Model – Big Data Analytics Tutorial

WordCount Program in Java Hadoop MapReduce Model – Big Data Analytics Tutorial

HDFS User Commands – Big Data Analytics Tutorial

How to install and Configure Hadoop in Ubuntu Step by Step Procedure – Shortcut Method

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Using the Web GUI to Monitor the MapReduce Running Examples – Big Data Analytics Tutorial

Running Basic Hadoop Benchmarks – Big Data Analytics Tutorial

How to Run Hadoop MapReduce Examples – Big Data Analytics Tutorial

Debugging MapReduce Parallel Application – Big Data Analytics Tutorial

Module 2 – Data Processing Tools, Hadoop and YARN Administration

Following are the contents of module 2

In this module, you will study Essential Hadoop Tools such as Apache Pig, Apache Hive, Apache HBase, Apache Sqoop, and Apache Oozie. Also, Hadoop YARN Applications, Managing Hadoop with Apache Ambari, Basic Hadoop Administration Procedures are discussed.

Apache Sqoop – Hadoop Ecosystem – Big Data Analytics Tutorial

Apache Spoop steps to Import and Export data between Database and HDFS

Apache Flume Hadoop Ecosystem – Big Data Analytics Tutorial

Apache Pig Hadoop Ecosystem – Big Data Analytics Tutorial

Apache Oozie Hadoop Ecosystem – Big Data Analytics Tutorial

Apache Hive Hadoop Ecosystem – Big Data Analytics Tutorial

Apache HBase Hadoop Ecosystem – Big Data Analytics Tutorial

Apache YARN Resource Manager – Big Data Analytics Tutorial

Hadoop Yarn Administration – Big Data Analytics Tutorial

Apache Ambari GUI Based method to manage Hadoop Services and configuration of Hadoop

Module 3 – Business Intelligence, Data Warehousing, Data Mining, Data Visualization

Following are the contents of module 3

In this module, you will study, business Intelligence Concepts, and their applications. Important concepts such as Data Warehousing, Data Visualization, and Data Mining are discussed.

Business Intelligence – Big Data Analytics Tutorial

Business Intelligence Applications – Big Data Analytics Tutorial

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Introduction to Data Warehouse – Big Data Analytics Tutorial

Data Warehouse Architecture – Big Data Analytics Tutorial

Introduction to Data Mining – Big data analytics Tutorial

Introduction to Data Mining Techniques – Big Data Analytics Tutorial

Tools and Platforms for Data Mining – Big Data Analytics Tutorial

Cross Industry Standard Process for Data Mining – CRISP-DM – Big Data Analytics Tutorial

Myths and Mistakes in data Mining – Big Data Analytics Tutorial

Data Visualization in Data Mining – Big Data Analytics Tutorial

Module 4 – Decision Trees, Regression, Artificial Neural Networks, Cluster Analysis, Association Rule Mining

In module 4, different machine learning algorithms such as Decision Trees, Regression, Artificial Neural Networks, Cluster Analysis, Association Rule Mining are discussed.

Decision Tree with Solved Numerical Example – Big Data Analytics Tutorial

1. Decision Tree Solved Numerical Example for Play tennis dataset – Big Data Analytics Tutorial

2. Decision Tree Solved Numerical Example for the given Loan approval Data set- Big Data Analytics Tutorial

3. Decision Tree Solved Numerical Example for City Size, Avg. Income, Local Investors, LOHAS Awareness Data set – Big Data Analytics Tutorial

Regression Analysis – Big Data Analytics Tutorial

Linear Regression Numerical Example with one Independent Variable

Linear Regression Numerical Example with Multiple Independent Variables

Linear Regression Numerical Example with one Independent Variable using Microsoft Excel

Linear Regression Numerical Example with Multiple Independent Variable using Microsoft Excel

Introduction to Cluster analysis and K Means Algorithm – Big Data Analytics Tutorial

K Means Clustering Algorithm – Solved Numerical Example – Big Data Analytics Tutorial

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An Introduction to Artificial Neural Networks – Big Data AnalyticsTutorial

Introduction to Association Rule Mining and Apriori Algorithm – Big Data Analytics Tutorial

Association Rule Mining – Apriori Algorithm – Numerical Example Solved – Big Data Analytics Tutorial

Association Rule Mining-Apriori Algorithm – Solved Numerical Example

Module 5 – Text Mining, Naïve Bayes Analysis, Support Vector Machine, Web Mining, and Social Network Analysis

In module 5, important concepts of Text Mining discussed. Later how to apply Naïve-Bayes Analysis on sample textual data for classification discussed. The concepts of Support Vector Machines are discussed in detail. Finally, you will understand, how Web Mining and Social Network Analysis are performed.

Text Mining Process Term Document Matrix Advantages Disadvantages of Text Mining

Naïve Bayes Model Big Data Analytics Tutorial by Mahesh Huddar

Solved Example Text Analytics or Text Classification using Naïve Bayes Classifier

Introduction to Support Vector Machine – Big Data Analytics – Machine Learning

Solved Support Vector Machine – Linear SVM Example – Big Data Analytics Tutorial

Solved Support Vector Machine – Non-Linear SVM Example – Big Data Analytics Tutorial

Click the below link to download the 2017 Scheme 17CS82 Big Data Analytics VTU CBCS Notes

M-1, M-2, M-3, M-4 and M-5

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2018 Scheme Computer Science and Engineering VTU CBCS Notes

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